• DocumentCode
    42412
  • Title

    Advances in Probabilistic Modeling: Applications of Stochastic Geometry [From the Guest Editors]

  • Author

    Adams, Martin ; Vo, Ba-Ngu ; Mahler, Ronald

  • Author_Institution
    Professor of Electrical Engineering, Universidad de Chile, Santiago, 837-0451, Chile
  • Volume
    21
  • Issue
    2
  • fYear
    2014
  • fDate
    Jun-14
  • Firstpage
    21
  • Lastpage
    24
  • Abstract
    The articles in this special section advocate that the same principle applies to feature detection and autonomous mapping in robotics, where, instead of referring to the problem of target estimation, the problem of map feature or environmental object estimation are of concern. From here on, map features, targets, and environmental objects of interest will simply be referred to as ???features.??? In the case of robotic mapping and SLAM, realistic feature detection algorithms produce false alarms and missed detections, and estimating the true number of map features is, therefore, central to these problems.
  • Keywords
    Estimation; Feature extraction; Geometry; Modeling; Probabilistic logic; Simultaneous localization and mapping; Special issues and sections; Stochastic systems; Terrain mapping;
  • fLanguage
    English
  • Journal_Title
    Robotics & Automation Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9932
  • Type

    jour

  • DOI
    10.1109/MRA.2014.2314018
  • Filename
    6827353